import sys,os
sys.path.append(os.pardir)
import numpy as np 
import matplotlib.pyplot as plt
from common.gradient import numerical_gradient

def gradient_descent(f,init_x,lr=0.01,step_num=100):
    x = init_x
    x_history = []

    for i in range(step_num):
        x_history.append(x.copy())

        grad = numerical_gradient(f,x)
        x -= lr*grad 
    return x,np.array(x_history)

def function_2(x):
    return x[0]**2+x[1]**2


init_x = np.array([-3.0,4.0])
lr = 0.1
step_num = 20
x,x_history = gradient_descent(function_2,init_x,lr=lr,step_num=step_num)

print(x)

plt.plot([-5,5],[0,0],'--b')
plt.plot([0,0],[-5,5],'--b')
plt.plot(x_history[:,0],x_history[:,1],'o')

plt.xlim(-3.5,3.5)
plt.ylim(-4.5,4.5)
plt.xlabel("X0")
plt.ylabel("X1")
plt.show()